Choice of study design randomized and non randomized approaches
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PAHO/PAHEF WORKSHOP EDUCATION FOR CHILDHOOD OBESITY PREVENTION: A LIFE-COURSE APPROACH Aruba, June 2012. Choice of study design: randomized and non-randomized approaches. Iná S. Santos Federal University of Pelotas Brazil. Outline of the presentation. Introduction Types of evidence

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Choice of study design randomized and non randomized approaches

PAHO/PAHEF WORKSHOP EDUCATION FOR CHILDHOOD OBESITY PREVENTION: A LIFE-COURSE APPROACHAruba, June 2012

Choice of study design: randomized and non-randomized approaches

Iná S. Santos

Federal University of Pelotas

Brazil


Outline of the presentation

Outline of the presentation

  • Introduction

    • Types of evidence

    • Internal and external validity

  • Randomized controlled trials

  • Non-randomized designs

  • Victora et al. Evidence-based Public Health: moving beyond randomized trials. Am J Public Health 2004;94(3):400-405

  • Habicht JP et al. Evaluation designs for adequacy, plausibility and probability of public health programme performance and impact. Intern J Epidemiology 1999;28:10-18


Part i

Part I

  • Introduction

    • Types of evidence

    • Internal and external validity


Types of epidemiological evidence for public health

Types of epidemiological evidence for Public Health


Valididy internal and external

Valididy: internal and external

External population

Target population

Actual population

Sample


Validity

Validity

  • Internal validity

    • Are the study results true for the target population?

    • Are there errors that affect the study findings?

      • Systematic error (bias, confounding)

      • Random error (precision)

  • External validity

    • Generalizability

    • Are the study results applicable to other settings?


Validity1

Validity

  • Internal validity

    • May be judged on the basis of the study methods

  • External validity

    • Require a “value judgment”


Part ii

Part II

Randomized controlled trials

(RCTs)


Internal validity in probability studies

Internal validity in probability studies

RCTs are the gold standard for internal validity


Rct from cochrane collaboration

RCT (from Cochrane Collaboration)

  • In a RCT participants are assigned by chance to receive either an experimental or control treatment.

  • When a RCT is done properly, the effect of a treatment can be studied in groups of people who are the same at the outset, and treated in the same way, except for the intervention being studied.

  • Any differences then seen in the groups at the end of the trial can be attributed to the difference in treatment alone, and not to bias or chance.


Randomised controlled trials

Randomised controlled trials

  • Prioritise internal validity

    • random allocation reduces selection bias and confounding

    • blinding reduces information bias

  • Gained popularity through clinical trials of new drugs

  • Essential for determining efficacy of new biological agents

  • Adequate for short causal chains

    • biological effects of drugs, vaccines, nutritional supplements, etc.

drug  pharmacological reaction disease cure or alleviation


Pooling data from rcts

Pooling data from RCTs

  • Systematic review

    • Comprehensive search for all high-quality scientific studies on a specific subject

      • E.g. on effects of a drug, vaccine, surgical technique, behavioral intervention, etc

  • Meta-analysis

    • Groups data from different studies to determine an average effect

    • Improves the precision of the available estimates by including a greater number of people

    • But: data from different studies cannot always be combined


What does a rct show

The probability that the observed result is due to the intervention

But additional evidence is required to make this result conceptually plausible

Biological plausibility

Operational plausibility

What does a RCT show?


Special issues in rcts

Special issues in RCTs

  • “Intent-to-treat” analyses

    • Individuals/groups should remain in the group to which they were originally assigned

  • Units of analyses

    • It is incorrect to use group allocation (e.g., health centers, communities, etc) and to analyse the data at individual level

    • This has implications for sample size calculation and for analysis methods


Consort statement

CONSORT Statement

  • Allocation

  • Rationale

  • Eligibility

  • Interventions

  • Objectives

  • Outcomes

  • Sample size

  • Randomization

    • Sequence generation

    • Concealment

    • Implementation

    • Blinding (masking)

  • Statistical methods

  • Participant flow

  • Recruitment

  • Baseline data

  • Numbers analyzed

  • Outcomes and estimation

  • Ancillary analyses

  • Adverse events

  • Interpretation

  • Generalizability

  • Overall evidence


Major steps in public health trials

Major steps in Public Health trials

  • Central-level provision of intervention to local outlets (e.g. health facilities)

  • Local providers’ compliance with delivery of intervention

  • Recipient compliance with intervention

  • Biological effect of intervention

Source: Victora, Habicht, Bryce, AJPH 2004


Example of public health intervention nutrition counselling trial

Central team

is competent

HWs are

trainable

Equipment is

available

Utilization

is adequate

Food is

available

Lack of food

is a cause of

malnutrition

Example of Public Health Intervention: Nutrition Counselling Trial

National programme is implemented

Health workers are trained

HW knowledge increases

HW performance improves

Maternal knowledge increases

Child diets change

Energy intake increases

Nutritional status improves

Source: Santos, Victora et al. J Nutr 2001


Example of public health intervention nutrition counselling trial1

Example of Public Health Intervention: Nutrition Counselling Trial

National programme is implemented

Health workers are trained

HW knowledge increases

0.807=0.21

HW performance improves

Maternal knowledge increases

Child diets change

Energy intake increases

Nutritional status improves

Source: Santos, Victora et al. J Nutr 2001


Are rct findings generalizable to routine programmes

The dose of the intervention may be smaller

behavioural effect modification

provider behaviour

recipient behaviour

The dose-response relationship may be different

biological effect modification

Are RCT findings generalizable to routine programmes?

The longer the causal chain, the more likely is effect modification

Source: Victora, Habicht, Bryce, AJPH 2004


Curvilinear associations

Curvilinear associations

Trials often

done here

Results often

applied here

Source: Victora, Habicht, Bryce, AJPH 2004


Why do rcts have a limited role in large scale effectiveness evaluations

Why do RCTs have a limited role in large-scale effectiveness evaluations

  • Often impossible to randomize

    • unethical, politically unacceptable, rapid scaling up

  • Evaluation team affects service delivery

    • service delivery is at least “best-practice”

  • Effect modification is the rule

    • are meta-analyses of complex programmes meaningful?

    • need for local data

  • Need for supplementary approaches for evaluations in Public Health


Part iii

Part III

Non-randomized designs

(Quasi-experiments)


Types of inference in impact evaluations

Types of inference in impact evaluations

  • Adequacy (descriptive studies)

    • the expected changes are taking place

  • Plausibility (observational studies)

    • observed changes seem to be due to the programme

  • Probability (RCTs)

    • randomised trial shows that the programme has a statistically significant impact

Source: Habicht, Victora, Vaughan, IJE 1999


Ensuring internal validity in probability and plausibility studies

Ensuring internal validity in probability and plausibility studies


Adequacy evaluations

Adequacy evaluations

  • Questions:

    • Were the initial goals achieved?

      • E.g.: reduce underfive mortality by 20%

    • Were the observed trends in impact indicators

      • in the expected direction?

      • of adequate magnitude?


Plausibility evaluations

Plausibility evaluations

  • Question:

    • Is the observed impact likely due to the intervention?

  • Require ruling out influence of external factors:

    • need for comparison group

    • adjustment for confounders

  • Also known as quasi-experiments


Adequacy plausibility designs 1

Adequacy/plausibility designs (1)

  • Design: cross-sectional

  • Measurement points: once

  • Outcome: difference or ratio

  • Control group:

    • Individuals who did not receive the intervention

    • Groups/areas without the intervention

    • Dose-response analyses, if possible


Ort and diarrhea deaths in brazil

ORT and diarrhea deaths in Brazil

Each dot = 1 state

Spearman r=-0,61 (p=0,04)


Adequacy plausibility designs 2

Adequacy/plausibility designs (2)

  • Design: longitudinal (before-and-after)

  • Measurement points: twice or more

  • Outcome: change

  • Control group:

    • The same or similar individuals, before the intervention

    • The same groups/areas, before the intervention

    • Time-trend analyses, if possible


Hib vaccine in uruguay

Hib vaccine in Uruguay

In Uruguay, reported Hib cases declined by over 95 percent after the introduction of routine infant Hib immunisation in 1994.

Source: PAHO, 2004


Adequacy plausibility designs 3

Adequacy/plausibility designs (3)

  • Design: longitudinal-control

  • Measurement points: twice or more

  • Outcome: relative change

  • Control group:

    • The same or similar individuals, before the intervention

    • The same groups/areas, before the intervention

    • Time-trend analyses, if possible


Adequacy plausibility designs 4

Adequacy/plausibility designs (4)

  • Design: case-control

  • Measurement points: once

  • Comparison: exposure to intervention

  • Groups:

    • Cases: individuals with the disease of interest

    • Controls: sample of the population from which cases originated


Choice of study design randomized and non randomized approaches

Stunting in Tanzania

Stunting prevalence among children aged 24-59 months

p (mean haz)

= 0.05

Source: Schellenberg J et al


Choice of study design randomized and non randomized approaches

  • Transparent Reporting for Evaluations with Nonrandomised Designs (TREND)

  • Similar to CONSORT guidelines

  • Include

    • conceptual frameworks used

    • intervention and comparison conditions

    • research design

    • methods of adjusting for possible biases

  • AJPH, March 2004

Source: Des Jarlais, Lyles, Crepaz and the TREND Group, AJPH 2004


Conclusions 1

Conclusions (1)

  • RCTs are essential for

    • clinical studies

    • community studies for establishing the efficacy of relatively simple interventions

  • RCTs require additional evidence from non-randomised studies for increasing their external validity


Conclusions 2

Conclusions (2)

  • Given the complexity of many Public Health interventions, adequacy and plausibility studies are essential in different populations

    • even for interventions proven by RCTs

  • Adequacy evaluations should become part of the routine of decision-makers

    • and plausibility evaluations too, when possible


Choice of study design randomized and non randomized approaches

THANK YOU


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